There are many existing methods for reducing the VLSI implementation cost of the adaptation arithmetic in stochastic gradient adaptive filters. Some of them cause significant performance impairments (such as slower convergence or increased misadjustment noise). However the replacement of multiplications by Power-of-Two Quantisers (PTQ), together with shifters, has been shown to reduce cost with very little performance impairment. This paper reviews an older method, Power-of-Two Multiplication (PTM), which is equivalent to exponent-only floating-point multiplication. We show that although it has little or no advantage over the PTQ approach for the LMS, NLMS, and GAL algorithms, the PTM method has significant advantages for implementing the m...
An LMS adaptive digital filter using distributed arithmetic (DA-ADF) has been proposed. Cowan and ot...
This paper presents a new algorithm that can solve the problem of selecting appropriate update step ...
The rate of convergence and the computational complexity of an adaptive algorithm are two essential ...
Abstract- In digital filter, when the coefficients assume power-of-two or a sum of power-of-two term...
This work deals with the use of previous or colateral information to improve the behaviour of adapti...
This work deals with the use of previous or colateral information to improve the behaviour of adapti...
Digital filters with power-of-two or a sum of power-of-two coefficients can be built using simple an...
Least Mean Square (LMS) filters are the most used adaptive filters with applications ranging from ch...
The effects of DC offsets on four variations of the stochastic gradient algorithm are analyzed to de...
This paper investigates the use of approximate fixed-width and static segment multipliers in the des...
The affine combination of two adaptive filters that simultaneously adapt on the same inputs has been...
The LMS algorithm invented by Widrow and Hoff in 1959 is the simplest, most robust, and one of the m...
A new adaptive filter algorithm has been developed that combines the benefits of the Least Mean Squa...
Adaptive filters that self-adjust their transfer functions according to optimizing algorithms are po...
A general formulation for developing a fast block-LMS adaptive algorithm is presented. In this algor...
An LMS adaptive digital filter using distributed arithmetic (DA-ADF) has been proposed. Cowan and ot...
This paper presents a new algorithm that can solve the problem of selecting appropriate update step ...
The rate of convergence and the computational complexity of an adaptive algorithm are two essential ...
Abstract- In digital filter, when the coefficients assume power-of-two or a sum of power-of-two term...
This work deals with the use of previous or colateral information to improve the behaviour of adapti...
This work deals with the use of previous or colateral information to improve the behaviour of adapti...
Digital filters with power-of-two or a sum of power-of-two coefficients can be built using simple an...
Least Mean Square (LMS) filters are the most used adaptive filters with applications ranging from ch...
The effects of DC offsets on four variations of the stochastic gradient algorithm are analyzed to de...
This paper investigates the use of approximate fixed-width and static segment multipliers in the des...
The affine combination of two adaptive filters that simultaneously adapt on the same inputs has been...
The LMS algorithm invented by Widrow and Hoff in 1959 is the simplest, most robust, and one of the m...
A new adaptive filter algorithm has been developed that combines the benefits of the Least Mean Squa...
Adaptive filters that self-adjust their transfer functions according to optimizing algorithms are po...
A general formulation for developing a fast block-LMS adaptive algorithm is presented. In this algor...
An LMS adaptive digital filter using distributed arithmetic (DA-ADF) has been proposed. Cowan and ot...
This paper presents a new algorithm that can solve the problem of selecting appropriate update step ...
The rate of convergence and the computational complexity of an adaptive algorithm are two essential ...